基于电子鼻的香蕉储存时间鉴别方法研究

研究了一种基于电子鼻系统的香蕉储存时间鉴别方法。实验检测了不同储存时间的香蕉样品,主成分分析方法可以较好地区分不同储存时间的香蕉样品,同时检验了样品的微生物指标以探讨电子鼻响应与微生物指标之间的关系。随机共振信噪比谱不但可以区分香蕉样品,同时基于信噪比特征值建立的香蕉储存时间鉴别模型具有较高的预测准确率。该方法具有较好的实际应用价值。     

基于电子鼻系统的番茄苗不同种类损伤的区分效果研究

通过对早疫病病害番茄苗、灰霉病病害番茄苗、机械损伤番茄苗和对照番茄苗的电子鼻响应信号的对比,可以看出不同处理的番茄苗样本电子鼻的响应信号是不同的,表明用电子鼻响应信号对番茄苗不同种类损伤进行预测是可行的.从PCA结果来看,早疫病病害的番茄苗和灰霉病病害的番茄苗能很好区分开,机械损伤的番茄苗和正常处理的番茄苗产生了重叠现...     

基于图像分割的扭曲鼻纹识别模型仿真

鼻纹特征是当前最新研究的生物识别特征,对身份的鉴定有着重要的意义.鼻子的纹路较细小,只有在挤压过程中,才能留下纹理特征.但是,挤压过程本身对特征就形成了一定的破坏,使得特征扭曲变形,无法形成完整特征.传统的生物识别方法多是依靠完整生物特征,在鼻纹特征残缺或者挤压造成特征形变的情况下,虽然能识别出特征,但是对应过程会产生大量的干扰,造成假识别,漏识别的问题.提出采用鼻纹图像小区域分割的扭曲识别方法.针对扭曲鼻纹图像进行矩阵重组,根据重组结果进行分割,完成扭曲鼻纹图像的分类,利用自适应迭代出不同区域的识别阀值,设定识别过程中的最优阀值,最终完成扭曲鼻纹图像的识别.仿真结果表明,利用改进算法进行扭曲鼻纹图像识别,能够有效提高识别的准确率.     

虚拟仪器技术在电子鼻中的应用

虚拟仪器技术是当今测试技术的发展方向。为了能够迅速建立一个可靠的数据采集系统,运用LabVIEW 7.0设计了测试应用程序,运用动态链接库技术,在程序中加入了判别算法。并在建立系统的过程中,通过分析和实验解决了一些实际问题。实验结果表明:系统符合设计要求。     

灰色理论在电子鼻气体定量分析中的应用

将气体传感器阵列与灰色系统理论相结合,设计出用于气体定量分析的电子鼻。根据传感器数列得到的实验数据为基础数据建立了气体定量分析的灰色预测模型GM（1,N）,并通过该模型对气体的体积分数进行了分析。实验证明：灰色系统理论用于气体的定量分析是可行的。     

A novel humid electronic nose combined with an electronic tongue for assessing deterioration of wine

We report herein the use of a combined system for the analysis of the spoilage of wine when in contact with air. The system consists of a potentiometric electronic tongue and a humid electronic nose. The potentiometric electronic tongue was built with thick-film serigraphic techniques using commercially available resistances and conductors for hybrid electronic circuits; i.e. Ag, Au, Cu, Ru, AgCl, and C. The humid electronic nose was designed in order to detect vapours that emanate from the wine and are apprehended by a moist environment. The humid nose was constructed using a piece of thin cloth sewn, damped with distilled water, forming five hollows of the right size to introduce the electrodes. In this particular case four electrodes were used for the humid electronic nose: a glass electrode, aluminium (Al), graphite and platinum (Pt) wires and an Ag-AgCl reference electrode. The humid electronic nose together with the potentiometric electronic tongue were used for the evaluation of the evolution in the course of time of wine samples. Additionally to the analysis performed by the tongue and nose, the spoilage of the wines was followed via a simple determination of the titratable (total) acidity.     

Discrimination of green tea quality using the electronic nose technique and the human panel test, comparison of linear and nonlinear classification tools

Electronic nose (E-nose) technique was attempted to discriminate green tea quality instead of human panel test in this work. Four grades of green tea, which were classified by the human panel test, were attempted in the experiment. First, the E-nose system with eight metal oxide semiconductors gas sensors array was developed for data acquisition; then, the characteristic variables were extracted from the responses of the sensors; next, the principal components (PCs), as the input of the discrimination model, were extracted by principal component analysis (PCA); finally, three different linear or nonlinear classification tools, which were K-nearest neighbors (KNN), artificial neural network (ANN) and support vector machine (SVM), were compared in developing the discrimination model. The number of PCs and other model parameters were optimized by cross-validation. Experimental results showed that the performance of SVM model was superior to other models. The optimum SVM model was achieved when 4 PCs were included. The back discrimination rate was equal to 100% in the training set, and predictive discrimination rate was equal to 95% in the prediction set, respectively. The overall results demonstrated that E-nose technique with SVM classification tool could be successfully used in discrimination of green tea's quality, and SVM algorithm shows its superiority in solution to classification of green tea's quality using E-nose data.     

蒸发温度对电子鼻白酒评价的影响研究

采用气体传感器阵列对7种市售白酒进行了动态测量,并研究蒸发温度对白酒识别分类的影响.白酒样本分别在20,40,60,80℃蒸发后进行测量,在每个蒸发温度下结合主元分析(PCA)法,分析了传感器阵列信号与白酒的香型和酒精度特征之间的关系,以及所有白酒样本按蒸发温度划分的结果.结果表明:按香型和酒精度划分,60℃的分类结果...     

Preparation, characterisation and applications of thin films for gas sensors prepared by cheap chemical method

The physical properties of pure and doped (Ni, Os, Pd and Pt) SnO₂ thin films, prepared by using a chloride-based inorganic sol–gel route, have been reported. These properties were investigated by using differential scanning calorimetry and thermogravimetric (DSC/TG), FTIR, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD) and atomic force microscopy (AFM) techniques. Microsensors for gas detection were also fabricated and tested in various atmospheres (nitrogen oxide, carbon monoxide, ethanol, methanol and methane). The dopants affected the coating properties depending on the formation of nanoparticles. Furthermore the gas-sensing properties towards reducing and oxidising gases were found to be dependent on the nature of doping element. An array consisting of the manufactured sensors has been arranged and examples of applications for “electronic nose” are given.